Analysis of LPC/DFT features for an HMM-based alphadigit recognizer

Daniel J. Mashao, Yoshihiko Gotoh, Harvey F. Silverman

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


The search for better and more robust performance of speech recognition systems is ongoing. Much of the improvement is likely to come from better acoustic feature analysis. In this letter, the results from a significant experiment are reported; these show how a warped-DFT analysis outperforms an LPC-cepstral analysis in a significant way, supporting results by other researchers for different recognition tasks. An analysis of nasal-letter performance is used to show the development of the warped-DFT feature analysis.

Original languageEnglish
Pages (from-to)103-106
Number of pages4
JournalIEEE Signal Processing Letters
Issue number4
Publication statusPublished - Apr 1996
Externally publishedYes

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics


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